Please use this identifier to cite or link to this item: http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/7682
Title: Optimised plasma sample preparation and LC‐MS analysis to support large‐scale proteomic analysis of clinical trial specimens: Application to the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial
Authors: O’Rourke, Matthew B.
GALANDE, SANJEEV et al.
Dept. of Biology
Keywords: Plasma
Mass spectrometry
Proteomics
Biomarker
Diabetes
Fenofibrate
2023-MAR-WEEK4
TOC-MAR-2023
2023
Issue Date: May-2023
Publisher: Wiley
Citation: Proteomics - Clinical Applications, 17(03).
Abstract: Purpose Robust, affordable plasma proteomic biomarker workflows are needed for large-scale clinical studies. We evaluated aspects of sample preparation to allow liquid chromatography-mass spectrometry (LC-MS) analysis of more than 1500 samples from the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial of adults with type 2 diabetes. Methods Using LC-MS with data-independent acquisition we evaluated four variables: plasma protein depletion, EDTA or citrated anti-coagulant blood collection tubes, plasma lipid depletion strategies and plasma freeze–thaw cycles. Optimised methods were applied in a pilot study of FIELD participants. Results LC-MS of undepleted plasma conducted over a 45 min gradient yielded 172 proteins after excluding immunoglobulin isoforms. Cibachrome-blue-based depletion yielded additional proteins but with cost and time expenses, while immunodepleting albumin and IgG provided few additional identifications. Only minor variations were associated with blood collection tube type, delipidation methods and freeze–thaw cycles. From 65 batches involving over 1500 injections, the median intra-batch quantitative differences in the top 100 proteins of the plasma external standard were less than 2%. Fenofibrate altered seven plasma proteins. Conclusions and clinical relevance A robust plasma handling and LC-MS proteomics workflow for abundant plasma proteins has been developed for large-scale biomarker studies that balance proteomic depth with time and resource costs.
URI: https://doi.org/10.1002/prca.202200106
http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/7682
ISSN: 1862-8346
1862-8354
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